Shandong Science ›› 2023, Vol. 36 ›› Issue (6): 1-7.doi: 10.3976/j.issn.1002-4026.2023.06.001

• Oceanographic Science, Technology and Equipment •     Next Articles

Survey of underwater biological object detection methods based on deep learning

YU Yu1a,1b(), GUO Baoqi2, CHU Shibo1a,1b, LI Heng1a,1b, YANG Pengru1a,1b   

  1. 1. a. Institute of Oceanographic Instrumentation;b. National Marine Monitoring Equipment Engineering Technology Research Center,Qilu University of Technology(Shandong Academy of Sciences),Qingdao 266100,China
    2. Qingdao Haida Xinxing Software Consulting Co., Ltd., Qingdao 266114, China
  • Received:2023-01-07 Online:2023-12-20 Published:2023-12-07


Underwater biological object detection is crucial for aquaculture, endangered species protection,and ecological environment monitoring. This study comprehensively analyzes the applications of various deep learning methods in underwater biological object detection. The commonly used underwater biological object detection datasets are introduced. The state-of-the-art underwater biological object detection methods are classified, analyzed, and summarized by two stages and one stage. The actual applications of various detection methods are thoroughly described, and the advantages and disadvantages of their optimization strategies are analyzed and summarized. Future works in the field of underwater biological object detection based on deep learning are presented. This study provides a reference basis for researchers in the field of underwater biological object detection.

Key words: deep learning, object detection, underwater biological object detection

CLC Number: 

  • TP181